Despite rapid advances in the state of the art of 3D computer visualization, the ability to unfold and flatten cortical surfaces that are obtained from PED, fMRI or other sources remains a major priority in all studies of cortical brain imaging. There are at two reasons for this statement: 1.) It is difficult or impossible to view the pattern of cortical activity which is embedded in the highly convoluted surface of the human neo-cortex without unfolding the surface. 2.) Patterns of functional architecture, such as cortical topography, are very difficult to model on three dimensional surfaces. Since the intrinsic curvature of the cortex is relatively small, it is possible to construct a flat map of individual brain regions. The goal of the present application is to apply recent progress in optimization technology to develop an accurate, rapid, progressively refinable method for unfolding and flattening cortical surfaces reconstructed from data obtained as tissue sections or from tomographic (e.g. PET, CAT, MRI and fMRI) imaging technologies. At present, there are no existing methods for cortical unfolding which are both accurate and rapid, and most methods in use are neither accurate nor rapid. These methods will be validated for accuracy and speed and the software developed will be distributed at moderate cost to interested users in academic and industrial laboratories. PROPOSED COMMERCIAL APPLICATION: Since current software for unfolding and flattening cortical data obtained in brain imagery studies is inaccurate and extremely slow, a moderately priced software package that accomplishes these goals with accuracy and rapid execution will have a wide market among laboratories using PETT, MRI, and other imaging modalities.